Binary Logistic Regression

Binary Logistic Regression is a statistical modeling technique that belongs to the class of generalized linear models, distinguished by its use of the logistic function to model the probability of a binary outcome variable as a function of one or more predictor variables.

5.6K

Publications

222.3K

Citations

25.4K

Authors

5.3K

Institutions

Publications per year

2017–2026

3.6K

Variants

Binomial Logistic Regression

Authors

25.4K

  1. BO
    Bright Opoku Ahinkorah

    University of Technology Sydney, Australia

    54 publications · 1.7K citations

    27

    h-index

  2. AS
    Abdul‐Aziz Seidu

    University of Cape Coast, Ghana

    45 publications · 1.3K citations

    25

    h-index

  3. EK
    Edward Kwabena Ameyaw

    University of Technology Sydney, Australia

    31 publications · 968 citations

    22

    h-index

  4. SY
    Sanni Yaya

    University of Ottawa, Canada

    22 publications · 834 citations

    18

    h-index

  5. EB
    Eugene Budu

    University of Cape Coast, Ghana

    22 publications · 615 citations

    17

    h-index

1–5 of 25.4K

Venues

  1. PLoS ONE

    267 publications · 11.1K citations

    56

    h-index

  2. BMC Public Health

    133 publications · 6.9K citations

    45

    h-index

  3. 38

    h-index

  4. PubMed

    Repository · 128 publications · 3.9K citations

    33

    h-index

  5. BMC Pregnancy and Childbirth

    46 publications · 2.3K citations

    29

    h-index

1–5